Abstract
Psychophysiological measures and artificial neural networks were used to determine how well higher levels of cognitive activity, such as executive function, spatial and verbal working memory and global workload, could be assessed. A complex uninhabited air vehicle simulator was used in which subjects were responsible for four vehicles simultaneously. The subjects had to evaluate visual images and maintain the status of the vehicles. The results showed that the cognitive states, derived from subjective reports, could be accurately classified. These results have application in human factors environments which demand higher level cognitive processing and may be useful when implementing adaptive aiding in these systems.
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